Information extraction (IE) addresses the problem of extracting specific information from a collection of documents. Much of the previous work for IE from structured documents formatted in HTML or XML uses techniques for IE from strings, such as grammar and automata induction. However, such documents have a tree structure. Hence it is natural to investigate methods that are able to recognise and exploit this tree structure. We do this by exploring the use of tree automata for IE in structured documents. Experimental results on benchmark data sets show that our approach compares favorably with previous approaches.
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